Background: The traditional anti-inflammation disease-modifying anti-rheumatic drugs (DMARDs) have limited therapeutic effects in rheumatoid arthritis (RA) patients. We previously reported the safety and efficacy of umbilical cord mesenchymal stem cell (UC-MSC) treatment in RA patients that were observed for up to 8 months after UC-MSC infusion. The aim of this study is to assess the long-term efficacy and safety of UC-MSC along with DMARDs for the treatment of RA. Methods: 64 RA patients aged 18–64 years were recruited in the study. During the treatment, patients were treated with 40 mL UC-MSC suspension product (2 × 10⁷ cells/20 mL) via intravenous injection immediately after the infusion of 100 mL saline. The serological markers tests were used to assess safety and the 28-joint disease activity score (DAS28) and the Health Assessment Questionnaire (HAQ) to assess efficacy. Results: 1 year and 3 years after UC-MSC cells treatment, the blood routine, liver and kidney function and immunoglobulin examination showed no abnormalities, which were all in the normal range. The ESR, CRP, RF of 1 year and 3 years after treatment and anti-CCP of 3 years after treatment were detected to be lower than that of pretreatment, which showed significant change (P < 0.05). Health index (HAQ) and joint function index (DAS28) decreased 1 year and 3 years after treatment than before treatment (P < 0.05). Conclusion: UC-MSC cells plus DMARDs therapy can be a safe, effective and feasible therapeutic option for RA patients.

While the RT-PCR is the silver bullet test for confirming the COVID-19 infection, it is limited by the lack of reagents, time-consuming, and the need for specialized labs. As an alternative, most of the prior studies have focused on Chest CT images and Chest X-Ray images using deep learning algorithms. However, these two approaches cannot always be used for patients’ screening due to the radiation doses, high costs, and the low number of available devices. Hence, there is a need for a less expensive and faster diagnostic model to identify the positive and negative cases of COVID-19. Therefore, this study develops six predictive models for COVID-19 diagnosis using six different classifiers (i.e., BayesNet, Logistic, IBk, CR, PART, and J48) based on 14 clinical features. This study retrospected 114 cases from the Taizhou hospital of Zhejiang Province in China. The results showed that the CR meta-classifier is the most accurate classifier for predicting the positive and negative COVID-19 cases with an accuracy of 84.21%. The results could help in the early diagnosis of COVID-19, specifically when the RT-PCR kits are not sufficient for testing the infection and assist countries, specifically the developing ones that suffer from the shortage of RT-PCR tests and specialized laboratories.

Tumor drug resistance presents a growing challenge in medical practice, particularly during anti-cancer therapies, where the emergence of drug-resistant cancer cells significantly complicates clinical treatment. In recent years, three-dimensional (3D) tumor culture technology, which more effectively simulates the in vivo physiological environment, has gained increasing attention in tumor drug resistance research and clinical applications. By mimicking the in vivo cellular microenvironment, 3D tumor culture technology not only recapitulates cell-cell interactions but also more faithfully reproduces the biological effects of therapeutic agents. Consequently, 3D tumor culture technology is emerging as a crucial tool in biomedical and clinical research. We summarize the benefits of 3D culture models and organoid technology, explore their application in the realm of drug resistance, drug screening, and personalized therapy, and discuss their potential application prospects and challenges in clinical transformation, with the aim of providing insights for optimizing cancer treatment strategies and advancing precision therapy.

Traditional tumor models cannot perfectly simulate the real state of tumors in vivo, resulting in the termination of many clinical trials. 3D tumor models’ technology provides new in vitro models that bridge the gap between in vitro and in vivo findings, and organoids maintain the properties of the original tissue over a long period of culture, which enables extensive research in this area. In addition, they can be used as a substitute for animal and in vitro models, and organoids can be established from patients’ normal and malignant tissues, with unique advantages in clinical drug development and in guiding individualized therapies. 3D tumor models also provide a promising platform for high-throughput research, drug and toxicity testing, disease modeling, and regenerative medicine. This report summarizes the 3D tumor model, including evidence regarding the 3D tumor cell culture model, 3D tumor slice model, and organoid culture model. In addition, it provides evidence regarding the application of 3D tumor organoid models in precision oncology and drug screening. The aim of this report is to elucidate the value of 3D tumor models in cancer research and provide a preclinical reference for the precise treatment of cancer patients.

Head and neck malignant tumors have numerous locations of the disease. After patients receive radiotherapy, their nutritional status is very poor, thus the curative effect is unsatisfactory. The aims of the present study were to investigate and analyze the nutritional status of patients with head and neck cancer undergoing radiotherapy (RT) in order to provide positive nutrition intervention for assisting the radiotherapy effect. A total of 40 patients with head and neck cancer were selected using a method of subjective global assessment (SGA) to assess nutritional status, including calorie intake and energy expenditure. In a randomized, controlled study, 20 patients received intensive dietary counseling and nutritional therapy (G1) and 20 received regular dietary as controls (G0) preradiotherapy and postradiotherapy. The primary endpoint was calorie intake and energy expenditure. The secondary endpoint was SGA rating with nutritional therapy. At the end of RT, energy intake showed a net increase in G1 (1,691±301 kcal) compared with that in G0 (1,066±312 kcal) (P<0.05); energy expenditure increased in G1 (1,673±279 kcal) compared with G0 (1,490±298 kcal) (P<0.05). The prevalence of severe malnutrition following radiotherapy was significantly different between the two study groups (10 patients in G0 and 4 patients in G1; P<0.05). The number of the normal malnutrition patients postRT in G0 decreased from 4 to 2 and conversely, in G1 it increased from 3 to 6 (P<0.05). In conclusion, patients with head and neck cancer were most malnutritioned, which impacted on clinical outcome. Timely nutritional intervention can effectively prevent weight loss and muscle wasting. Additionally, it may improve quality of life by decreasing the frequency of severe malnutrition.